Agentsop Crewai
agentsope/SkillAlchemy
SOP for building multi-agent systems with CrewAI — role-based collaboration, sequential/hierarchical processes, Flows, memory, delegation.
Generate YAML configuration files and run CLI commands to onboard organizations into ModelGuide.
$ npx skills add modelguide/modelguide --skill mg-cli -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install modelguide/modelguide mg-cli --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/modelguide/modelguide.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/mg-cli .claude/skills/mg-cli && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "mg-cli" agent skill from https://github.com/modelguide/modelguide/tree/main/.claude/skills/mg-cli into .claude/skills/mg-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mg-cli", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/modelguide/modelguide/tree/main/.claude/skills/mg-cliType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add modelguide/modelguide --skill mg-cli -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install modelguide/modelguide mg-cli --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/modelguide/modelguide.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/mg-cli .agents/skills/mg-cli && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mg-cli" agent skill from https://github.com/modelguide/modelguide/tree/main/.claude/skills/mg-cli into .agents/skills/mg-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mg-cli", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add modelguide/modelguide --skill mg-cli -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install modelguide/modelguide mg-cli --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/modelguide/modelguide.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/mg-cli .cursor/skills/mg-cli && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mg-cli" agent skill from https://github.com/modelguide/modelguide/tree/main/.claude/skills/mg-cli into .cursor/skills/mg-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mg-cli", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/modelguide/modelguide.git --path .claude/skills/mg-cli--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add modelguide/modelguide --skill mg-cli -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install modelguide/modelguide mg-cli --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/modelguide/modelguide.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/mg-cli .gemini/skills/mg-cli && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mg-cli" agent skill from https://github.com/modelguide/modelguide/tree/main/.claude/skills/mg-cli into .gemini/skills/mg-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mg-cli", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install modelguide/modelguide mg-cliInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add modelguide/modelguide --skill mg-cli -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/modelguide/modelguide.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/mg-cli .github/skills/mg-cli && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mg-cli" agent skill from https://github.com/modelguide/modelguide/tree/main/.claude/skills/mg-cli into .github/skills/mg-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mg-cli", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add modelguide/modelguide --skill mg-cli -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install modelguide/modelguide mg-cli --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/modelguide/modelguide.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/mg-cli .opencode/skills/mg-cli && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mg-cli" agent skill from https://github.com/modelguide/modelguide/tree/main/.claude/skills/mg-cli into .opencode/skills/mg-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mg-cli", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
mg-cliGenerate YAML configuration files and run CLI commands to onboard organizations into ModelGuide.
Mg CLI is an agent skill from modelguide/modelguide. Generate YAML configuration files and run CLI commands to onboard organizations into ModelGuide. Use this skill when the user asks to set up an org, create agents, import SOPs, add connectors, prepare onboarding YAML, provision a customer, seed demo data, or anything related to the mg CLI tool. Also trigger when the user mentions "mg setup", "mg import", "mg add", "onboard", "provision org", "create YAML for CLI", "prepare config files", or asks how to get a new organization running in ModelGuide.
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/catalog.md`, `references/examples.md` and `references/schemas.md`).
It sits in AI & LLM Engineering, covering Operations and SOPs and Building AI agents. The repository describes itself as: Open-source voice agent orchestration framework - build production voice AI pipelines without vendor lock-in. The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 554caa0. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
bunrailwayFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
store.acme.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
APP_DB_PASSWORDFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Mg CLI loads about 3.5k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 128 tokens; SKILL.md has 663 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from modelguide/modelguide at commit 554caa0, republished under its MIT licence (© modelguide). 663 words, ~3,471 tokens.
.claude/skills/mg-cli/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.The mg CLI is a thin orchestration layer over ModelGuide's service layer. It reads YAML files, validates them with Zod, and calls existing @features/* services in dependency order. All business logic lives in the services — the CLI handles parsing, validation, orchestration, and output.
mg setup pipelineThere are two ways to use the CLI:
Create a directory with YAML files anywhere on disk, then run one command:
cd modelguide-api
bun run src/cli/mg.ts setup /path/to/my-org/ # provision everything
bun run src/cli/mg.ts setup /path/to/my-org/ --dry-run # validate and preview without changesThe directory can live anywhere — it does not need to be inside the modelguide repo. Pass an absolute or relative path.
Required file: org.yaml
Optional files: users.yaml, secrets.yaml, connectors.yaml, agents.yaml, sops.yaml, guardrails.yaml, evals.yaml (or evals-*.yaml for multi-agent orgs), sessions.yaml
Flags:
--dry-run — validate all YAML files against schemas and print the plan without touching the database. Use this to verify files are correct before running for real.--skip-secrets — use placeholder values (useful for CI/testing)--skip-compile — skip agent compilation step--skip-evals — skip eval import--skip-sessions — skip demo session importRun each step separately (useful for adding to an existing org):
cd modelguide-api
bun run src/cli/mg.ts create-org --from /path/to/org.yaml
bun run src/cli/mg.ts add-users --org acme --from /path/to/users.yaml
bun run src/cli/mg.ts add-secrets --org acme --from /path/to/secrets.yaml
bun run src/cli/mg.ts add-connectors --org acme --from /path/to/connectors.yaml
bun run src/cli/mg.ts add-agents --org acme --from /path/to/agents.yaml
bun run src/cli/mg.ts import-sops --org acme /path/to/sops.yaml
bun run src/cli/mg.ts import-guardrails --org acme /path/to/guardrails.yaml
bun run src/cli/mg.ts import-evals --org acme /path/to/evals.yaml
bun run src/cli/mg.ts compile-agents --org acme
bun run src/cli/mg.ts import-sessions --org acme /path/to/sessions.yamlThe order matters because later steps reference entities created earlier:
1. org.yaml — organization (everything scoped to this)
2. users.yaml — users (agents need a createdBy user)
3. secrets.yaml — standalone secrets (connectors may reference these)
4. connectors.yaml — connectors + connector-scoped secrets
5. agents.yaml — agents + tool assignments (references connectors)
6. sops.yaml — SOPs (references agents + connector tools)
7. guardrails.yaml — guardrails (references agents)
8. evals.yaml — eval suites, evaluators, test cases (references agents + SOPs)
9. compile-agents — compiles each agent against its active SOPs (skipped with --skip-compile)
10. sessions.yaml — demo sessions (references agents)The mg setup command handles this order automatically and threads an IdRegistry (slug-to-UUID map) across all steps so cross-references resolve without extra DB queries.
Re-running is safe:
externalId in JSONB; eval configs by nameexternalId (explicit or derived from payload hash)--skip-secrets on re-runs)Each YAML file has a specific structure. For the complete field-by-field reference with types, defaults, constraints, and edge cases, read references/schemas.md.
name: "Acme Corp"
slug: "acme" # lowercase + hyphens only
timezone: "America/Chicago" # optional
features: [voice-agents] # optional
demoEnabled: false # optional, default falseusers:
- email: admin@acme.example.com
name: "Alice Admin"
role: admin # admin | supportsecrets:
- name: OpenAI API Key
type: platform_api_key # api_key | oauth_token | credentials | platform_api_key | webhook_secret
scope: agent # connector | agent (optional)
# value: omitted = prompted interactively (or placeholder with --skip-secrets)# Real connector — references a registered TypeScript manifest
connectors:
- name: "Acme Store"
slug: "acme_store" # lowercase + underscores
catalogSlug: "medusa" # must match a catalog entry — see references/catalog.md
config:
baseUrl: "https://api.acme.example.com"
secrets: # connector-scoped secrets created automatically
- field: "secretApiKey" # field name in connector config
name: "Acme Store API Key"
type: api_key
# Mocked connector — DB-driven fixtures, no TypeScript handler (ADR-013)
- name: "Bank Nowa Banking (Mock)"
slug: "banknowa_banking"
isMocked: true # switches schema branch
iconUrl: "/logos/bank-nowa.svg" # optional
tools: # inline tool defs — each returns `mock_response` verbatim
- name: "Verify Customer"
description: "Verify identity."
input_schema:
type: object
properties: { name: {type: string} }
required: [name]
mock_response:
success: true
customer_id: "CUST-001"Edit mock_response in YAML and re-run mg add-connectors — existing tool rows are reconciled (no delete-then-reimport needed). See references/schemas.md for full field tables.
agents:
- name: "Acme Voice Agent"
slug: "acme-voice-agent"
description: "Handles phone orders"
modality: voice # voice | text (default: voice)
platform: custom # custom | elevenlabs | livekit (default: custom)
tools:
- connectorSlug: "acme_store" # all tools from this connector
- connectorSlug: "acme_support"
toolSlugs: [create_ticket, get_ticket] # specific tools onlyFor platform: livekit (voice-test + outbound dispatch require this):
agents:
- name: "Acme Voice Agent"
slug: "acme-voice-agent"
modality: voice
platform: livekit
config:
# Only url + agentName are valid for livekit. llmModel is rejected
# (baked into the worker image).
url: "wss://your-project.livekit.cloud"
agentName: "acme_voice_agent" # must match the profile key in the worker's config/agents.yaml
tools:
- connectorSlug: "acme_store"
secrets:
# No `value:` → `mg setup` prompts once per field. These exact field
# names are read by agents.service.ts:getAgentSecretByType when
# dispatching the worker.
- field: livekit_api_key
name: "LiveKit API Key"
type: api_key
- field: livekit_api_secret
name: "LiveKit API Secret"
type: api_keyInline SOP (define steps directly):
sops:
- name: "Order Lookup"
slug: "order-lookup"
status: active # draft | active | archived (default: draft)
agents: ["acme-voice-agent"]
trigger:
type: intent_detected # see references/schemas.md for all trigger types
config:
patterns: ["where is my order", "track my order", "order status"]
steps:
- id: greet
instruction: "Greet and ask for order number"
required: true
- id: lookup
instruction: "Look up the order"
required: true
tool:
connectorSlug: "acme_store"
toolSlug: "get_order"Template fork (fork from a global SOP template):
sops:
- name: "Order Lookup"
templateSlug: "order-lookup" # must match a template — see references/catalog.md
status: active
agents: ["acme-voice-agent"]
connectorMapping:
medusa: "acme_store" # maps template's catalog refs to org's connector slugsCannot specify both templateSlug and steps.
guardrails:
- name: "No Medical Claims"
slug: "no-medical-claims"
content: |
Never claim any product treats, cures, or prevents a medical condition.
description: "FDA compliance"
config: { priority: critical, category: compliance }
agents: ["acme-voice-agent", "acme-chat-assistant"]One file per agent. For multi-agent orgs, use multiple files: evals-insurance.yaml, evals-booking.yaml, etc. The mg setup pipeline globs for evals*.yaml.
agentSlug: acme-voice-agent
evaluators:
- name: confirms-order-id
criterion: Agent confirms the order ID back to the customer
tags: [accuracy] # optional
- name: does-not-fabricate
criterion: Agent does NOT make up order details or tracking information
tags: [compliance, accuracy] # optional
test_cases:
- id: order-lookup-happy-path-01
sop_slug: order-lookup
scenario_key: order_status # optional
tags: [order-lookup, happy-path] # optional
evaluators: # references by name
- confirms-order-id
- does-not-fabricate
input:
customer_message: Hi, I placed an order last week, number ACM-12345.
conversation_history:
- role: assistant
content: Thanks for calling Acme Corp. How can I help you today?Also supports standalone import via JSON (eval-scenarios.json) with --agent flag:
bun run src/cli/mg.ts import-evals --org acme --agent acme-voice-agent /path/to/eval-scenarios.jsonsessions:
- agentSlug: "acme-voice-agent"
channel: voice # voice | web | api | slack | widget | sms | whatsapp | email
status: completed # active | completed | abandoned (default: completed)
userIdentifier: "sarah@example.com"
hoursAgo: 2 # how far back to timestamp messages (default: 1)
messages:
- role: user
content: "Hi, I want to check on my order ORD-1234."
- role: assistant
content: "Let me look that up for you."
feedback: # optional
verdict: good # good | bad
comment: "Very helpful"
source: customer # customer | support | system
links: # optional
- url: "https://store.acme.com/orders/1234"
title: "Order ORD-1234"
resourceType: "order"When the user describes their organization, follow this process:
~/onboarding/my-customer/)cd modelguide-api && bun run src/cli/mg.ts setup /path/to/dir --dry-run--skip-secrets for testing, or run without flags for productionFor the full schema reference with every field, type, and constraint, read references/schemas.md.
For available connector catalog entries and SOP templates, read references/catalog.md.
For a complete working example (Acme Corp), read references/examples.md.
All commands must be run from the modelguide-api/ directory:
cd modelguide-api
bun run src/cli/mg.ts <command> [options]Running against Railway (from your local machine):
cd modelguide-api
railway run --service api -- sh -c \
'DATABASE_URL=postgresql://modelguide_app:$APP_DB_PASSWORD@$POSTGRES_TCP_PROXY_DOMAIN:$POSTGRES_TCP_PROXY_PORT/$PGDATABASE \
bun run src/cli/mg.ts setup /path/to/my-org/ --skip-secrets'railway run injects all env vars (secrets, encryption keys, etc.). DATABASE_URL is overridden with the public TCP proxy since the private hostname isn't reachable locally. Requires TCP proxy vars from railway/DEPLOY.md step 6.
Add a single agent to an existing org:
bun run src/cli/mg.ts add-agents --org acme name="New Agent" slug=new-agent modality=voiceCompile only one agent:
bun run src/cli/mg.ts compile-agents --org acme --agent acme-voice-agentImport SOPs without activating (review first):
Set status: draft in sops.yaml, import, review in dashboard, then activate manually.
Re-run after fixing a YAML error: Safe to re-run — duplicates are skipped. Only new entities get created.
© modelguide, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (references) in .claude/skills/mg-cli of modelguide/modelguide.
Open the folder on GitHubat commit 554caa0
Mg CLI next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mg CLI this skillmodelguide/modelguide | 108 | — | ~3.5k | Automated safety check: Pass | MIT | |
| Agentsop Crewaiagentsope/SkillAlchemy | 457 | — | ~4.8k | Automated safety check: Pass | MIT | |
| Agentsop Dspyagentsope/SkillAlchemy | 457 | — | ~7k | Automated safety check: Pass | MIT | |
| Agentsop Idempotent Ingestionagentsope/SkillAlchemy | 457 | — | ~6.8k | Automated safety check: Pass | MIT | |
| Agent Creatoraiskillstore/marketplace | 430 | 1 repos | ~4.8k | Automated safety check: Pass | None | |
| Agentsop Difyagentsope/SkillAlchemy | 457 | — | ~5.4k | Automated safety check: Notes | MIT |
agentsope/SkillAlchemy
SOP for building multi-agent systems with CrewAI — role-based collaboration, sequential/hierarchical processes, Flows, memory, delegation.
agentsope/SkillAlchemy
Operating SOP for DSPy (Stanford NLP) — the declarative framework for "programming, not prompting" language models.
agentsope/SkillAlchemy
Re-ingest-correctness SOP for production RAG. An agent skill from agentsope/SkillAlchemy.
aiskillstore/marketplace
Creates specialized AI agents with optimized system prompts using the official 4-phase SOP methodology from Desktop .claude-flow, combined with evidence-based prompting techniques and Claude Agent…
agentsope/SkillAlchemy
SOP for building LLM applications on Dify — visual workflow + chatflow + agent + RAG knowledge base + plugin marketplace + observability, self-hostable.
agentsope/SkillAlchemy
Neutral, framework-agnostic decision tree for project kickoff: "which agent / RAG / LLM framework should I reach for?" Synthesizes the ecosystem sections of 7 landmark-project SOPs (LangGraph…
modelguide/modelguide
A skill your agent uses when the user asks to add a connector, create a connector, implement a connector for a service, add a tool to a connector, update a connector tool, or asks about connector…
modelguide/modelguide
Use before committing significant code changes to verify project integrity.
modelguide/modelguide
Trigger phrases - "reset local db", "recreate local postgres", "restore dump to local", "reset local database", "load backup locally"
modelguide/modelguide
Backup a PostgreSQL database from a Railway environment. An agent skill from modelguide/modelguide.
modelguide/modelguide
Restore a PostgreSQL database backup to a Railway environment.
modelguide/modelguide
Deploy all ModelGuide services (API, UI, LB) to a Railway environment.
Generate YAML configuration files and run CLI commands to onboard organizations into ModelGuide. Mg CLI is an agent skill from modelguide/modelguide. Generate YAML configuration files and run CLI commands to onboard organizations into ModelGuide.
Mg CLI fits situations like: the user asks to set up an org; prepare onboarding YAML; provision a customer; anything related to the mg CLI tool.
Run `npx skills add modelguide/modelguide --skill mg-cli -a claude-code`. Or copy the skill folder (.claude/skills/mg-cli in modelguide/modelguide) into .claude/skills/mg-cli in your project. Claude Code loads it when a task matches its description.
Run `npx skills add modelguide/modelguide --skill mg-cli -a codex`. Or copy the skill folder (.claude/skills/mg-cli in modelguide/modelguide) into .agents/skills/mg-cli in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add modelguide/modelguide --skill mg-cli -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mg-cli, .gemini/skills/mg-cli, .github/skills/mg-cli and .opencode/skills/mg-cli in your project.
Going by SKILL.md and its folder, Mg CLI needs the command-line tools its instructions call (bun and railway) and credentials named APP_DB_PASSWORD.
SKILL.md names 1 domain. In commands or code: store.acme.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Mg CLI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 9.1k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Mg CLI: Agentsop Crewai (agentsope/SkillAlchemy, 457 stars), Agentsop Dspy (agentsope/SkillAlchemy, 457 stars), Agentsop Idempotent Ingestion (agentsope/SkillAlchemy, 457 stars) and Agent Creator (aiskillstore/marketplace, 430 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
modelguide (a GitHub organization) maintains it in modelguide/modelguide, which has 108 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on June 20, 2026.
Source: modelguide/modelguide on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.